SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

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Showing 1201–1225 of 7282 papers

TitleStatusHype
Spatial-Spectral Transformer for Hyperspectral Image DenoisingCode1
TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape GenerationCode1
A Neural-Network-Based Convex Regularizer for Inverse ProblemsCode1
Adaptive Dynamic Filtering Network for Image DenoisingCode1
3D Detection and Characterisation of ALMA Sources through Deep LearningCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
DiffStyler: Controllable Dual Diffusion for Text-Driven Image StylizationCode1
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property PredictionCode1
Statistically unbiased prediction enables accurate denoising of voltage imaging dataCode1
Self-Supervised Image Restoration with Blurry and Noisy PairsCode1
Denoising diffusion models for out-of-distribution detectionCode1
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud LearningCode1
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal RecommendationCode1
DPCSpell: A Transformer-based Detector-Purificator-Corrector Framework for Spelling Error Correction of Bangla and Resource Scarce Indic LanguagesCode1
From Denoising Diffusions to Denoising Markov ModelsCode1
A Simple and Robust Correlation Filtering Method for Text-based Person SearchCode1
Galaxy Image Deconvolution for Weak Gravitational Lensing with Unrolled Plug-and-Play ADMMCode1
On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT SettingCode1
Intelligent Painter: Picture Composition With Resampling Diffusion ModelCode1
MagicMix: Semantic Mixing with Diffusion ModelsCode1
SG-VAD: Stochastic Gates Based Speech Activity DetectionCode1
Diffiner: A Versatile Diffusion-based Generative Refiner for Speech EnhancementCode1
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detectionCode1
Deep Equilibrium Approaches to Diffusion ModelsCode1
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified